BEMPS Bozen Economics & Management Paper Series NO 35/ 2016 An investigation on tourism farms in South Tyrol Maria Giovanna Brandano, Linda Osti, Manuela Pulina
An investigation on tourism farms in South Tyrol Maria Giovanna Brandano, Linda Osti and Manuela Pulina Abstract This study is based on data collected at a sample of agritourism located in South Tyrol (Italy). Though a probabilistic modelling, based on a cluster and a PCA it is possible to investigate the determinants that influence the probability to choose one of the two types of agritourism. The results show that motivations related to nature and authenticity positively influence customers choice of a farm that engages in the tourism activity. However, perceived negative externalities negatively influence the choice of this type of farms. Keywords: Agritourism, South Tyrol, probabilistic modelling. Jel Classification: C38, L83, Z32. 1. Introduction The number of agritourism farms in Italy has constantly increased in the last years. This fact confirms the Italian trend observed in recent time regarding the diversification in the accommodation supply. Indeed, it is recorded on the one hand the decrease in the number of traditional hotels, on the other hand the increase in the number of alternative forms of accommodation, in particular Bed & Breakfast and agritourism infrastructures (Candela and Figini, 2010). Moreover, the Travel & Tourism Competitiveness Report (WEF, 2015) shows that Italy represents one of the most competitive countries in the world (ranked 2 nd ) for natural tourism. With the growing demand of rural living for relaxation and recreational purposes, the potential market for agritourism is increasing. Agritourism can be described as a combination of tourist activities that combine rural living, passive or active involvement of guests in farming activities, local culture, and genuine food. Italy represents the first tourist destination for food and wine vacations proposed by international tour operators. Moreover, in the last years this type of tourism is rising at a rate of 12% per year (ISNART, 2013) and can be Department of Economics and Business, University of Sassari and CRENOS, Via Muroni 25, 07100 Sassari, Italy, Email: mgbrandano@uniss.it. School of Economics and Management, Free University of Bozen/Bolzano, Piazza Università 1, I-39100 Bozen/Bolzano, Italy, E-mail: Linda.Osti@unibz.it Department of Political Sciences (POLCOMING) & CRENoS, University of Sassari, Piazza Università, 11, 07100 Sassari, Italy, E-mail: mpulina@uniss.it 1
considered more resilient to the economic crisis than other forms of tourism. The link between food and wine and vacations includes agritourism. Amongst the Italian regions, the autonomous province of South Tyrol ranks second for the number of agritorusm in 2014 (Istat, 2015), after Tuscany. According to Santeramo and Barbieri (2015) further research is needed to show the characteristics of the demand while controlling for different types of settings, motivations, as well as tourism flows (e.g., local and international tourists). The present paper goes a step further within this thread of literature by analyzing supply and demand of agritourism within a joint framework in order to link motivations, satisfaction, perception on several externalities as well as different types of services offered by farmers. 2. The case study The present paper focuses on South Tyrol province. Tourism represents a significant driver for the regional economy. The accommodation supply is one of the largest in Italy; indeed, the region ranks second after Emilia Romagna for number of hotels. In terms of demand, in 2013 it ranked second for nights of stay with respect to other Italian regions, and in the last decade, tourist arrivals have recorded a high rate of growth. On average, statistics indicate that in this region tourist length of stay (approximately five days) is higher than in the other Italian regions, suggesting that this area is characterized by a high appeal as a tourist destination. Because tourists travel to South Tyrol mainly for the mountains, the landscape, the nature and the food and wine vacation, agritourisms play a key role in this sector. Agritourism activities in South Tyrol are more than 2,800 (Istat, 2015) and represent 15% of the total Italian supply. In the last ten years the total number of agritourism activities recorded a growth of, on average, 3% per year. The survey was divided into two parts. The first part interviewed sampled agritourism infrastructures located on the downs and the hilly areas of South Tyrol and collected information about the characteristics of the farms. During the telephone interview, agritourism infrastructures were asked for their cooperation in collecting self-administered questionnaires among their visitors. Interviewed visitors had to be tourists staying at the infrastructure for at least one night. Altogether, 26 infrastructures were interviewed and of these, 20 agreed upon cooperation to the second part of the survey for the collection of data among visitors. The second part of the survey involved the collection of data among the guests of the 2
sampled agritourism infrastructures. Altogether, 375 questionnaires were collected among the 20 infrastructures, who cooperated in the data collection. 3. Results To evaluate the determinants that are likely to influence customers choice on the type of agritourism farm, a probabilistic modelling is employed. In Table 1 the odds ratio are reported. An odds ratio less than one is associated with a coefficient with a negative sign, and in this case, the probability to choose a type of agritourism farm is less likely than the probability to choose the other. Alternatively, an odds ratio greater than one is associated with a coefficient with a positive sign and, in this case, the probability to choose a type of agritourism farm is more likely than the probability to choose the other. When the odds ratio is exactly one, this implies that the odds are even. For each of the models, marginal effects are also calculated to take into account the amount of change in the dependent variable. On this basis, the logit model is constructed on the dependent variable, obtained from the cluster analysis, as discussed previously, and defined as Y i = (Y 1, Y 2 ): Y 1 takes the value one if customer i chooses a tourism enthusiast farm; whereas, Y 2 takes the value zero, if customer i chooses a tourism opportunist farm. A general to specific approach is used, starting with an unrestricted specification that is then parsimoniously reduced to a final restricted model. Figure 1 represents a summary of the results the probabilistic models and show the determinants of choosing a tourism enthusiast farm over a tourism opportunist one. Figure 1. Determinants of consumers choice 3
4. Conclusions This paper provided an investigation on the determinants that influence consumers choice of agritourism farms in South Tyrol (Italy). Overall, general push motivations as well as the specific motivations related to nature and authenticity, were found to be the most relevant determinants that are likely to positively influence customers choice of a tourism enthusiast farm. However, perceived negative externalities negatively impact on the probability to choose this type of accommodation. References Candela G. and P. Figini (2010), Economia del turismo e delle destinazioni, McGraw-Hill, Milano. ISNART (2010), Indagine sul turismo organizzato internazionale, Unioncamere. ISTAT (2015), Capacità e movimento degli esercizi ricettivi. Santeramo FG. and C. Barbieri (2015). On the demand for agritourism: a cursory review of methodologies and practice. Tourism Planning and Development, DOI: 10.1080/21568316.2015.1137968. World Economic Forum, WEF (2015), The Travel & Tourism Competitiveness Report 2015, Ginevra. 4